240 research outputs found

    A Comprehensive Survey of Potential Game Approaches to Wireless Networks

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    Potential games form a class of non-cooperative games where unilateral improvement dynamics are guaranteed to converge in many practical cases. The potential game approach has been applied to a wide range of wireless network problems, particularly to a variety of channel assignment problems. In this paper, the properties of potential games are introduced, and games in wireless networks that have been proven to be potential games are comprehensively discussed.Comment: 44 pages, 6 figures, to appear in IEICE Transactions on Communications, vol. E98-B, no. 9, Sept. 201

    Review on Radio Resource Allocation Optimization in LTE/LTE-Advanced using Game Theory

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    Recently, there has been a growing trend toward ap-plying game theory (GT) to various engineering fields in order to solve optimization problems with different competing entities/con-tributors/players. Researches in the fourth generation (4G) wireless network field also exploited this advanced theory to overcome long term evolution (LTE) challenges such as resource allocation, which is one of the most important research topics. In fact, an efficient de-sign of resource allocation schemes is the key to higher performance. However, the standard does not specify the optimization approach to execute the radio resource management and therefore it was left open for studies. This paper presents a survey of the existing game theory based solution for 4G-LTE radio resource allocation problem and its optimization

    Radio resource allocation for uplink OFDMA systems with finite symbol alphabet inputs

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    In this paper, we consider the radio resource allocation problem for uplink orthogonal frequency-division multiple-access (OFDMA) systems. The existing algorithms have been derived under the assumption of Gaussian inputs due to its closed-form expression of mutual information. For the sake of practicality, we consider the system with finite symbol alphabet (FSA) inputs and solve the problem by capitalizing on the recently revealed relationship between mutual information and minimum mean square error (MMSE). We first relax the problem to formulate it as a convex optimization problem, and then, we derive the optimal solution via decomposition methods. The optimal solution serves as an upper bound on the system performance. Due to the complexity of the optimal solution, a low-complexity suboptimal algorithm is proposed. Numerical results show that the presented suboptimal algorithm can achieve performance very close to the optimal solution and that it outperforms the existing suboptimal algorithms. Furthermore, using our proposed algorithm, significant power saving can be achieved in comparison to the case when a Gaussian input is assumed

    Recent advances in radio resource management for heterogeneous LTE/LTE-A networks

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    As heterogeneous networks (HetNets) emerge as one of the most promising developments toward realizing the target specifications of Long Term Evolution (LTE) and LTE-Advanced (LTE-A) networks, radio resource management (RRM) research for such networks has, in recent times, been intensively pursued. Clearly, recent research mainly concentrates on the aspect of interference mitigation. Other RRM aspects, such as radio resource utilization, fairness, complexity, and QoS, have not been given much attention. In this paper, we aim to provide an overview of the key challenges arising from HetNets and highlight their importance. Subsequently, we present a comprehensive survey of the RRM schemes that have been studied in recent years for LTE/LTE-A HetNets, with a particular focus on those for femtocells and relay nodes. Furthermore, we classify these RRM schemes according to their underlying approaches. In addition, these RRM schemes are qualitatively analyzed and compared to each other. We also identify a number of potential research directions for future RRM development. Finally, we discuss the lack of current RRM research and the importance of multi-objective RRM studies

    A Distributed Game-Theoretic Solution for Power Management in the Uplink of Cell-Free Systems

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    This paper investigates cell-free massive multiple input multiple output systems with a particular focus on uplink power allocation. In these systems, uplink power control is highly non-trivial, since a single user terminal is associated with multiple intended receiving base stations. In addition, in cell-free systems, distributed power control schemes that address the inherent spectral and energy efficiency targets are desirable. By utilizing tools from game theory, we formulate our proposal as a noncooperative game, and using the best-response dynamics, we obtain a distributed power control mechanism. To ensure that this power control game converges to a Nash equilibrium, we apply the theory of potential games. Differently from existing gamebased schemes, interestingly, our proposed potential function has a scalar parameter that controls the power usage of the users. Numerical results confirm that the proposed approach improves the use of the energy stored in the battery of user terminals and balances between spectral and energy efficiency.Comment: Accepted at IEEE Globecom 202

    Distributed energy-aware resource allocation in multi-antenna multi-carrier interference networks with statistical CSI

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    Resource allocation for energy efficiency optimization in multi-carrier interference networks with multiple receive antennas is tackled. First, a one-hop network is considered, and then, the results are extended to the case of a two-hop network in which amplify-and-forward relaying is employed to enable communication. A distributed algorithm which optimizes a system-wide energy-efficient performance function, and which is guaranteed to converge to a stable equilibrium point, is provided. Unlike most previous works, in the definition of the energy efficiency, not only the users' transmit power but also the circuit power that is required to operate the devices is taken into account. All of the proposed procedures are guaranteed to converge and only require statistical channel state information, thus lending themselves to a distributed implementation. The asymptotic regime of a saturated network in which both the active users and the number of receive antennas deployed in each receiver grow large is also analyzed. Numerical results are provided to confirm the merits of the proposed algorithms
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